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CONTRIBUTING.md

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Yet Another Viral Subspecies Analysis Pipeline (YAVSAP): Contributing Guidelines

Hi there! Many thanks for taking an interest in improving YAVSAP.

We try to manage the required tasks for YAVSAP using GitHub issues, you probably came to this page when creating one. Please use the pre-filled template to save time.

However, don't be put off by this template - other more general issues and suggestions are welcome! Contributions to the code are even more welcome ;)

YAVSAP comforms to pipeline standards made by the nf-core group. These guidelines are a mix of general GitHub workflow, nf-core compliance, and our own way of doing things.

Contribution workflow

If you'd like to write some code for YAVSAP, the standard workflow is as follows:

  1. Check that there isn't already an issue about your idea in the ksumngs/yavsap issues to avoid duplicating work
    • If there isn't one already, please create one so that others know you're working on this
  2. Fork the ksumngs/yavsap repository to your GitHub account
  3. Make the necessary changes / additions within your forked repository following Pipeline conventions
  4. Use nf-core schema build and add any new parameters to the pipeline JSON schema (requires nf-core tools >= 1.10).
  5. Submit a Pull Request against the dev branch and wait for the code to be reviewed and merged

If you're not used to this workflow with git, you can start with some docs from GitHub or even their excellent git resources.

Tests

When you create a pull request with changes, GitHub Actions will run automatic tests. Typically, pull-requests are only fully reviewed when these tests are passing, though of course we can help out before then.

There are typically two types of tests that run:

Lint tests

nf-core has a set of guidelines which we strive to adhere to. To enforce these and ensure that all pipelines stay in sync, there is a helper tool which runs checks on the pipeline code. This is in the nf-core/tools repository and once installed can be run locally with the nf-core lint <pipeline-directory> command.

💡 To install nf-core tools on Linux or Mac, run the following commands

python3 -m pip install --user pipx
python3 -m pipx ensurepath
pipx install nf-core

If any failures or warnings are encountered, please follow the listed URL for more documentation.

Pipeline tests

We use the test dataset over at https://github.com/ksumngs/nf-test-datasets/tree/yavsap for testing. GitHub Actions then runs the pipeline on this data to ensure that it exits successfully. If there are any failures then the automated tests fail. These tests are run both with the latest available version of Nextflow and also the minimum required version that is stated in the pipeline code.

Patch

⚠️ Only in the unlikely and regretful event of a release happening with a bug.

  • On your own fork, make a new branch patch based on upstream/master.
  • Fix the bug, and bump version (X.Y.Z+1).
  • A PR should be made on master from patch to directly this particular bug.

Getting help

For further information/help, please consult the YAVSAP documentation.

Pipeline contribution conventions

To make the YAVSAP code and processing logic more understandable for new contributors and to ensure quality, we semi-standardise the way the code and other contributions are written.

Adding a new step

If you wish to contribute a new step, please use the following coding standards:

  1. Define the corresponding input channel into your new process from the expected previous process channel
  2. Write the process block (see below).
  3. Define the output channel if needed (see below).
  4. Add any new parameters to nextflow.config with a default (see below).
  5. Add any new parameters to nextflow_schema.json with help text (via the nf-core schema build tool).
  6. Add sanity checks and validation for all relevant parameters.
  7. Perform local tests to validate that the new code works as expected.
  8. If applicable, add a new test command in .github/workflow/ci.yml.
  9. Update MultiQC config assets/multiqc_config.yaml so relevant suffixes, file name clean up and module plots are in the appropriate order. If applicable, add a MultiQC module.
  10. Add a description of the output files and if relevant any appropriate images from the MultiQC report to docs/output.md.

Default values

Parameters should be initialised / defined with default values in nextflow.config under the params scope.

Once there, use nf-core schema build to add to nextflow_schema.json.

Default processes resource requirements

Every process definition should be specified with withLabel: selectors so they will request the proper amount of resources. A nf-core standard set of labels that should be followed where possible can be seen in the nf-core pipeline template, which has the default process as a single core-process, and then different levels of multi-core configurations for increasingly large memory requirements defined with standardised labels.

The process resources can be passed on to the tool dynamically within the process with the ${task.cpu} and ${task.memory} variables in the script: block.

Naming schemes

There are only two hard things in computer science: naming and cache invalidation. With regards to the later, in case of failure remove the -resume flag. With regards to the former, we name things slightly different from nf-core's guidelines. Specifically, we use these naming guidelines:

  • Use UPPER_CASE_WITH_UNDERSCORE_SEPARATORS for Process and Workflow names
  • Use CapitalizeEveryWordWithoutSeparators for Channel and Global variable names
    • Exception: output channels
  • Use snake_case_underscore_separators for parameter and process label names, and input and output variable names

Nextflow version bumping

If you are using a new feature from core Nextflow, you may bump the minimum required version of nextflow in the pipeline with: nf-core bump-version --nextflow . [min-nf-version]

Images and figures

For overview images and other documents we follow the nf-core style guidelines and examples.